Distributional Spectral Diagnostics for Localizing Grokking Transitions
Fuente:
arXiv
Guardado en:
| Autores principales: | Wang, Ziyue, Ying, Yufeng, Kanamori, Takafumi |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Grokking in LLM Pretraining? Monitor Memorization-to-Generalization without Test
por: Li, Ziyue, et al.
Publicado: (2025)
por: Li, Ziyue, et al.
Publicado: (2025)
A Convex Framework for Confounding Robust Inference
por: Ishikawa, Kei, et al.
Publicado: (2023)
por: Ishikawa, Kei, et al.
Publicado: (2023)
Robust Estimation for Kernel Exponential Families with Smoothed Total Variation Distances
por: Kanamori, Takafumi, et al.
Publicado: (2024)
por: Kanamori, Takafumi, et al.
Publicado: (2024)
Mixture Proportion Estimation and Weakly-supervised Kernel Test for Conditional Independence
por: Hirose, Yushi, et al.
Publicado: (2026)
por: Hirose, Yushi, et al.
Publicado: (2026)
Grokking as a Variance-Limited Phase Transition: Spectral Gating and the Epsilon-Stability Threshold
por: Acharya, Pratyush, et al.
Publicado: (2026)
por: Acharya, Pratyush, et al.
Publicado: (2026)
TULiP: Test-time Uncertainty Estimation via Linearization and Weight Perturbation
por: Zhang, Yuhui, et al.
Publicado: (2025)
por: Zhang, Yuhui, et al.
Publicado: (2025)
Grokking as a Falsifiable Finite-Size Transition
por: Bi, Yuda, et al.
Publicado: (2026)
por: Bi, Yuda, et al.
Publicado: (2026)
To Grok Grokking: Provable Grokking in Ridge Regression
por: Xu, Mingyue, et al.
Publicado: (2026)
por: Xu, Mingyue, et al.
Publicado: (2026)
Grokking as Dimensional Phase Transition in Neural Networks
por: Wang, Ping
Publicado: (2026)
por: Wang, Ping
Publicado: (2026)
SpectralGap: Graph-Level Out-of-Distribution Detection via Laplacian Eigenvalue Gaps
por: Gu, Jiawei, et al.
Publicado: (2025)
por: Gu, Jiawei, et al.
Publicado: (2025)
Grokking as the Transition from Lazy to Rich Training Dynamics
por: Kumar, Tanishq, et al.
Publicado: (2023)
por: Kumar, Tanishq, et al.
Publicado: (2023)
Scaling-based Data Augmentation for Generative Models and its Theoretical Extension
por: Koike, Yoshitaka, et al.
Publicado: (2024)
por: Koike, Yoshitaka, et al.
Publicado: (2024)
The Complexity Dynamics of Grokking
por: DeMoss, Branton, et al.
Publicado: (2024)
por: DeMoss, Branton, et al.
Publicado: (2024)
Measuring Sharpness in Grokking
por: Miller, Jack, et al.
Publicado: (2024)
por: Miller, Jack, et al.
Publicado: (2024)
Weight Decay Regimes in Grokking Transformers: Cheap Online Diagnostics
por: Verma, Lucky
Publicado: (2026)
por: Verma, Lucky
Publicado: (2026)
Topological Signatures of Grokking
por: Tang, Yifan, et al.
Publicado: (2026)
por: Tang, Yifan, et al.
Publicado: (2026)
Bridging Lottery Ticket and Grokking: Understanding Grokking from Inner Structure of Networks
por: Minegishi, Gouki, et al.
Publicado: (2023)
por: Minegishi, Gouki, et al.
Publicado: (2023)
Information-Theoretic Progress Measures reveal Grokking is an Emergent Phase Transition
por: Clauw, Kenzo, et al.
Publicado: (2024)
por: Clauw, Kenzo, et al.
Publicado: (2024)
Feature Repulsion and Spectral Lock-in: An Empirical Study of Two-Layer Network Grokking
por: Xu, Yongzhong
Publicado: (2026)
por: Xu, Yongzhong
Publicado: (2026)
Grokked Models are Better Unlearners
por: Liang, Yuanbang, et al.
Publicado: (2025)
por: Liang, Yuanbang, et al.
Publicado: (2025)
Grokking as a First Order Phase Transition in Two Layer Networks
por: Rubin, Noa, et al.
Publicado: (2023)
por: Rubin, Noa, et al.
Publicado: (2023)
ILDR: Geometric Early Detection of Grokking
por: Golwala, Shreel
Publicado: (2026)
por: Golwala, Shreel
Publicado: (2026)
Exploring Grokking: Experimental and Mechanistic Investigations
por: Qiye, Hu, et al.
Publicado: (2024)
por: Qiye, Hu, et al.
Publicado: (2024)
GrokAlign: Geometric Characterisation and Acceleration of Grokking
por: Walker, Thomas, et al.
Publicado: (2025)
por: Walker, Thomas, et al.
Publicado: (2025)
Grokking in Linear Models for Logistic Regression
por: Das, Nataraj, et al.
Publicado: (2026)
por: Das, Nataraj, et al.
Publicado: (2026)
Grokking Explained: A Statistical Phenomenon
por: Carvalho, Breno W., et al.
Publicado: (2025)
por: Carvalho, Breno W., et al.
Publicado: (2025)
Controlling Grokking with Nonlinearity and Data Symmetry
por: Salah, Ahmed, et al.
Publicado: (2024)
por: Salah, Ahmed, et al.
Publicado: (2024)
Grokking of Diffusion Models: Case Study on Modular Addition
por: Kim, Joon Hyeok, et al.
Publicado: (2026)
por: Kim, Joon Hyeok, et al.
Publicado: (2026)
Explaining Grokking in Transformers through the Lens of Inductive Bias
por: Singh, Jaisidh, et al.
Publicado: (2026)
por: Singh, Jaisidh, et al.
Publicado: (2026)
Beyond Progress Measures: Theoretical Insights into the Mechanism of Grokking
por: Gu, Zihan, et al.
Publicado: (2025)
por: Gu, Zihan, et al.
Publicado: (2025)
Grokking Finite-Dimensional Algebra
por: Notsawo, Pascal Jr Tikeng, et al.
Publicado: (2026)
por: Notsawo, Pascal Jr Tikeng, et al.
Publicado: (2026)
Grokking Group Multiplication with Cosets
por: Stander, Dashiell, et al.
Publicado: (2023)
por: Stander, Dashiell, et al.
Publicado: (2023)
Muon Optimizer Accelerates Grokking
por: Tveit, Amund, et al.
Publicado: (2025)
por: Tveit, Amund, et al.
Publicado: (2025)
Robust VAEs via Generating Process of Noise Augmented Data
por: Irobe, Hiroo, et al.
Publicado: (2024)
por: Irobe, Hiroo, et al.
Publicado: (2024)
The Geometric Inductive Bias of Grokking: Bypassing Phase Transitions via Architectural Topology
por: Yıldırım, Alper
Publicado: (2026)
por: Yıldırım, Alper
Publicado: (2026)
Explaining Grokking and Information Bottleneck through Neural Collapse Emergence
por: Sakamoto, Keitaro, et al.
Publicado: (2025)
por: Sakamoto, Keitaro, et al.
Publicado: (2025)
Egalitarian Gradient Descent: A Simple Approach to Accelerated Grokking
por: Pasand, Ali Saheb, et al.
Publicado: (2025)
por: Pasand, Ali Saheb, et al.
Publicado: (2025)
Flatness is Necessary, Neural Collapse is Not: Rethinking Generalization via Grokking
por: Han, Ting, et al.
Publicado: (2025)
por: Han, Ting, et al.
Publicado: (2025)
When Data Falls Short: Grokking Below the Critical Threshold
por: Singh, Vaibhav, et al.
Publicado: (2025)
por: Singh, Vaibhav, et al.
Publicado: (2025)
Deep Grokking: Would Deep Neural Networks Generalize Better?
por: Fan, Simin, et al.
Publicado: (2024)
por: Fan, Simin, et al.
Publicado: (2024)
Ejemplares similares
-
Grokking in LLM Pretraining? Monitor Memorization-to-Generalization without Test
por: Li, Ziyue, et al.
Publicado: (2025) -
A Convex Framework for Confounding Robust Inference
por: Ishikawa, Kei, et al.
Publicado: (2023) -
Robust Estimation for Kernel Exponential Families with Smoothed Total Variation Distances
por: Kanamori, Takafumi, et al.
Publicado: (2024) -
Mixture Proportion Estimation and Weakly-supervised Kernel Test for Conditional Independence
por: Hirose, Yushi, et al.
Publicado: (2026) -
Grokking as a Variance-Limited Phase Transition: Spectral Gating and the Epsilon-Stability Threshold
por: Acharya, Pratyush, et al.
Publicado: (2026)